Discrete-Time Sliding Mode Predictive Control Based on Extended State Observer for Reference Tracking of Dynamic Positioning Ship

This paper introduces a sliding mode predictive control (SMPC) approach designed for the dynamic positioning of ships, addressing both model inaccuracies and environmental disturbances. The method combines sliding mode control with model predictive control (MPC) to achieve robust performance in the face of uncertainties. To further enhance system stability and convergence speed, an advanced nonlinear discrete-time sliding mode controller is proposed, incorporating an integral fast terminal term. This modification ensures quicker and more reliable convergence to the desired state, even under challenging conditions. In addition, an extended state observer (ESO) is employed to estimate the uncertainties in ship model parameters and external disturbances, enabling real-time adaptation to varying operational environments. The effectiveness and robustness of the proposed approach are demonstrated through simulation results, which show significant improvements in positioning accuracy and disturbance rejection compared to traditional control strategies.